The Effect of Using Digital Storytelling on Students' Reading Comprehension and Listening Comprehension

The purpose of this study was to find out the effect of using digital storytelling strategy on students' reading comprehension and listening comprehension. The design of this study was Quasi-Experimental with pretest and post-test. Thus, two classrooms containing the total of 60 students of level II at Language Development Center of UIN Suska Riau were selected as the sample based on their similar characteristics and were assigned into an experimental and a control group. In collecting the data, reading and listening tests as well as observations were utilized to assess participants' comprehension abilities prior to and after the treatment. In analyzing the data, the t-tests (paired sample, and independent sample) were run in SPSS. In addition, Cohen D formula was applied to determine the effect size. The results showed that there were no significant differences (p > 0.05) between the means of the pretests scores, and there were significant differences (p < 0.05) between the means of both groups post-tests scores, reading comprehension (p=0.02), and listening comprehension (p=0.04). In other words, the students' comprehension levels were similar prior to the treatment, and the students of the experimental group outperformed the control group after the treatment. In addition, the values of the effect size obtained, reading (0.5), and listening (0.5), were categorized into the moderate effect size. Thus it was inferred that the use of digital storytelling had a significant effect on students' reading and listening comprehension at Language Development Center of UIN Suska Riau

Comparing between Hysteresis Current Controller and Space Vector Modulation of Field Oriented Control when Driving PMSM

This Paper has been Blacklisted due to fake paymentnbspreceipt and fraud attempt to publish research paper

Spontaneous Pregnancy Outcome after Surgical Repair of Clinically Palpable Varicocele in Young Men with Abnormal Semen Analysis

Objective: The beneficial effect of varicocele repair in male infertility&nbsp; remains unresolved. The aim of this study was to identify the benefit from varicocele treatment based on pregnancy rate rather than improvement of semen quality.Subjects and Methods: This study included 141 infertile men with varicocele detected by clinical examination and confirmed by venous reflux on continuous wave Doppler ultrasonography (US). Measurement of Body Mass Index (BMI) and hormonal assays were performed in all patients. A total of 233 sub-inguinal varicocele repairs were done. Couples were followed up with semen analysis and pregnancy detection for 6, 12 and 18 months. Statistical analysis was performed using the chi-square, t-test and Mann-Whitney test where appropriate (p &lt;0.05 accepted as statistically significant).Results: The spontaneous pregnancy rate was significantly greater in men with low or normal BMI. There were statistically significant differences between postoperative mean sperm count (64.7&plusmn;6.8 and 10.5&plusmn;1.8&nbsp; million/ml) and progressive motility (38.3&plusmn;2.4 and 17.7&plusmn;1.8%) for&nbsp; spontaneous pregnancy and non-pregnancy, respectively. There were also significant changes from pre- to postoperative mean sperm concentration (21.5&plusmn;2.1 and 64.7&plusmn;3.8 million/ml), progressive motility (12.9&plusmn;1.8 and 31.7&plusmn;1.4%) and normal morphology (54&plusmn;1.3 and 81.3&plusmn;4.6%) in the spontaneous pregnancy cohort. Comparing pre- and postoperative serum hormone levels, FSH and prolactin decreased significantly in spontaneous pregnancy (6.57&plusmn;0.65 to 4.6&plusmn;0.53 IU/L and 166.2&plusmn;11.8 to 149.3&plusmn;10.4 pmol/L, respectively) and increased in non-pregnancy (9.05&plusmn;0.71 IU/L and 187.8&plusmn;13.3 pmol/L, respectively).Conclusion: Spontaneous pregnancy after sub-inguinal varicocelectomy is significantly affected by BMI, sperm concentration, progressive motility and morphology. The decrease of FSH may predict the spontaneous pregnancy outcome

The Development of a Predictive Theory of Science Education Based Upon Information Processing Theory

This thesis describes the establishment of a new predictive theory for science education which can give direction to the improvement and transformation of science teaching at all levels. It is based upon Information Processing Theory. It has the ability to predict performance in science on the basis of independent psychological tests and to provide a framework for understanding how scientific learning takes place. The development of the theory has resulted from empirical work on 529 school pupils at "0" Grade (age 16) and on 440 Glasgow University students, through two series of experiments in addition to two confirmatory studies in the U.S.A. and Egypt. The first series related to students performance in individual questions, and the second related to students over-all performance in conventional examinations. Throughout this empirical work, a constant pattern has emerged showing that the students' holding-thinking space limited their ability to solve problems of different complexity. As soon as there was an overload on students' holding-thinking space, their performance fell away. In addition, the students' holding-thinking space is considered to be a good predictor for success in the conventional "0" Grade examinations, as well as the university examinations not only in chemistry, but also in physics, biology and mathematics. Where the theory and the empirical measurements have not agreed exactly, further investigation has been done to examine the disparities. In some cases new understanding has occurred which has allowed the theory to be modified. This thesis illustrates the importance of the teaching of learning strategies. In fact, it raises the teaching of strategies on to a par with the teaching of content. Three ways of successfully reducing the load on the students' holding-thinking space have been described and tested. The effect of the limitation of students' perceptual fields and of holding-thinking space on learning and problem solving tasks is also explored. The theory, which has been established in this thesis, answered some of the questions that educators have concerning students' limitations in learning and in problem solving. The outworking of this theory in terms of instructional methods, design of computer programs, books and laboratory experiences, is forming the basis of several follow-up studies

Mapping and characterizing mangrove rice growing environments in West-Africa using remote sensing and secondary data

Rice is one of the major staple foods consumed in Africa and its demand continues to increase as a result of population growth, urbanization and changing diets. Mangrove rice cultivation is of importance along the West-African Atlantic coast from Senegal and Gambia down to Guinea-Bissau, Guinea-Conakry, Sierra Leone and Liberia. Although mangrove rice productivity is low it contributes for a major share to the regional rice production. Sea-level rise and reduction in river discharges, caused by the effects of climate change, lead to salt-water intrusion and are a potential threat to the mangrove rice production and regional food security. Information about rice areas is crucial to provide informed decision and management with the aim of safeguarding and improving rice production in those areas. However, till date such information is very limited or unavailable at all. Therefore our goal in this study was to map out rice cultivated areas within the mangrove ecosystem stretching from Senegal to Liberia and to characterize those systems in terms of altitude and the rice phenology using secondary data and spatial analysis. We deployed off-season Landsat 8 Images, 30 meters SRTM Digital elevation data, derived vegetation indices (EVI, SAVI, Tasseled cap Index Wetness) and Google Earth data. Decision tree classification was then applied using the DEM and Tasseled Cap index on Wetness to delineate the Landsat data into uplands and mangrove lowlands. Then, supervised classification using the ‘maximum likelihood’ classifier was applied on the delineated mangrove lowlands to characterize the area into rice and non-rice. The classification result was validated with Google Earth images. The second stage in this work was to investigate the rice phenology using MODIS NDVI time series. Overall, the study shows the potency of using medium resolution satellite images like Landsat for characterizing mangrove rice growing environment